Player
misha
Team Aether7Clutches won
1v3Best clutch won
0.93Rating
43Maps
0.90K/D
73.7ADR
56%HS
72%KAST
70–54Opening duels
By map
| Map | Maps | K/D | ADR |
|---|---|---|---|
| mirage | 9 | 0.89 | 74.3 |
| dust2 | 8 | 1.00 | 68.1 |
| ancient | 7 | 0.90 | 81.5 |
| train | 6 | 0.85 | 76.5 |
| inferno | 5 | 0.90 | 70.2 |
| anubis | 5 | 0.90 | 70.6 |
| nuke | 3 | 0.82 | 76.7 |
Last 20 maps
| Opponent | Map | K–D | ADR |
|---|---|---|---|
| BOSS | ancient | 13–16 | 78.0 |
| BOSS | dust2 | 7–15 | 48.4 |
| Outfit 49 | inferno | 8–10 | 53.3 |
| Outfit 49 | dust2 | 17–13 | 84.1 |
| Mythic | train | 16–13 | 68.8 |
| Mythic | mirage | 18–16 | 81.3 |
| FULL SEND | train | 12–21 | 63.4 |
| FULL SEND | inferno | 9–14 | 60.8 |
| FULL SEND | mirage | 11–15 | 57.1 |
| NRG | mirage | 26–25 | 94.8 |
| NRG | inferno | 7–16 | 41.6 |
| Lycus Empire | dust2 | 11–8 | 75.9 |
| Lycus Empire | inferno | 17–13 | 100.1 |
| Chicken Coop Esports | dust2 | 21–19 | 61.5 |
| Chicken Coop Esports | train | 9–14 | 53.2 |
| Supernova Comets | mirage | 12–15 | 56.2 |
| Supernova Comets | dust2 | 13–17 | 62.2 |
| BOSS | ancient | 12–18 | 74.6 |
| BOSS | train | 24–27 | 84.4 |
| exregain | anubis | 20–19 | 68.5 |
Team history
| Team | Maps | Period |
|---|---|---|
| Team Aether | 17 | 2025-07 – 2025-10 |
| Alter Iron Club | 16 | 2024-10 – 2025-02 |
| Locke's Kitten | 10 | 2024-06 – 2024-06 |
Career by year
| Year | Maps | Rating | ADR | KAST |
|---|---|---|---|---|
| 2025 | 31 | 0.92 | 71.9 | 71% |
| 2024 | 12 | 0.95 | 78.1 | 73% |
Rating by event
| Event | Maps | Rating | ADR | KAST |
|---|---|---|---|---|
| ESL Challenger League Season 50 - Cup #4 North America | 2 | 0.74 | 62.5 | 61% |
| ESL Challenger League Season 50 - Cup #2 North America | 7 | 0.91 | 67.0 | 74% |
| Thunderpick World Championship 2025 NA#2 | 8 | 0.91 | 69.0 | 70% |
| Champion of Champions Tour Season 2 - North America Series 4 | 14 | 0.96 | 77.1 | 71% |
| FragPhillyTap2 | 2 | 0.79 | 95.5 | 69% |
| Frag Kansas City | 10 | 0.98 | 75.3 | 74% |
ADR and KAST are our own calculations from round data. Rating is our calculation from round data (1.0 formula).
